AIMC Topic: Surveys and Questionnaires

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Understanding and detecting behaviours prior to a suicide attempt: A mixed-methods study.

The Australian and New Zealand journal of psychiatry
OBJECTIVE: Prior research suggests there are observable behaviours preceding suicide attempts in public places. However, there are currently no ways to continually monitor such sites, limiting the potential to intervene. In this mixed-methods study, ...

What do individuals with visual impairment need and want from a dialogue-based digital assistant?

Clinical & experimental optometry
CLINICAL SIGNIFICANCE: Optometrists are well-placed to provide helpful advice and guidance to patients with visual impairment but may not know how best to do this. The availability of a reliable and comprehensive conversational agent to which patient...

Development and validation of questionnaire-based machine learning models for predicting all-cause mortality in a representative population of China.

Frontiers in public health
BACKGROUND: Considering that the previously developed mortality prediction models have limited applications to the Chinese population, a questionnaire-based prediction model is of great importance for its accuracy and convenience in clinical practice...

A Survey on Low-Latency DNN-Based Speech Enhancement.

Sensors (Basel, Switzerland)
This paper presents recent advances in low-latency, single-channel, deep neural network-based speech enhancement systems. The sources of latency and their acceptable values in different applications are described. This is followed by an analysis of t...

[A survey study towards the opinions of clinicians, patients and care partners regarding computer tools in the memory clinic: sense or nonsense?].

Tijdschrift voor gerontologie en geriatrie
INTRODUCTION: Computer tools based on artificial intelligence could aid clinicians in memory clinics by supporting diagnostic decision-making and communicating diagnosis and prognosis. We aimed to identify preferences of end-users, and barriers and f...

Artificial Intelligence for Radiotherapy Auto-Contouring: Current Use, Perceptions of and Barriers to Implementation.

Clinical oncology (Royal College of Radiologists (Great Britain))
AIMS: Artificial intelligence has the potential to transform the radiotherapy workflow, resulting in improved quality, safety, accuracy and timeliness of radiotherapy delivery. Several commercially available artificial intelligence-based auto-contour...

A wholistic view of continual learning with deep neural networks: Forgotten lessons and the bridge to active and open world learning.

Neural networks : the official journal of the International Neural Network Society
Current deep learning methods are regarded as favorable if they empirically perform well on dedicated test sets. This mentality is seamlessly reflected in the resurfacing area of continual learning, where consecutively arriving data is investigated. ...

Artificial intelligence in radiology: trainees want more.

Clinical radiology
AIM: To understand the attitudes of UK radiology trainees towards artificial intelligence (AI) in Radiology, in particular, assessing the demand for AI education.

Long-term care insurance purchase decisions of registered nurses: Deep learning versus logistic regression models.

Health policy (Amsterdam, Netherlands)
OBJECTIVE: The purpose of this study was to use a deep learning model and a traditional statistical regression model to predict the long-term care insurance decisions of registered nurses.

Implementing machine learning methods with complex survey data: Lessons learned on the impacts of accounting sampling weights in gradient boosting.

PloS one
Despite the prominent use of complex survey data and the growing popularity of machine learning methods in epidemiologic research, few machine learning software implementations offer options for handling complex samples. A major challenge impeding th...